I think there are a lot of developers working in repos where it's almost guaranteed that their code will _not_ still be there in 10 years, or 5 years, or even 1 year.

I would classify all of those as "capabilities and limitations of your product"

I read OPs "good code" to mean "highly aesthetic code" (well laid out, good abstractions, good comments, etc. etc.), and in that sense I agree no customer who's just using the product actually cares about that.

Another definition of "good code" is probably "code that meets the requirements without unexpected behavior" and in that sense of course end users care about good code, but you could give me two black boxes that act the same externally, one written as a single line , single character variables, etc. etc. etc. and another written to be readable, and I wouldn't care so long as I wasn't expected to maintain it.

I really don't see how this can be possible unless they're accepting abysmal recall? Perhaps I'm missing something fundamental here, but the idea that AI and non-AI assisted text can be separated with "nearly 0 false positives" just says to me that it's really just a filter for the weakest, most obvious AI generated text. Is that valuable?

In my own tests the emergent drama/gameplay has been pretty fun to watch, so I wanted to share it with the world. It's open-source, so feel free to make changes: https://github.com/MPWhite/agent-empire

Comments URL: https://news.ycombinator.com/item?id=47567416

Points: 4

# Comments: 0

The tool today measures high level signals (typing consistency, paste %, edit rate ,etc.) to give a score. After writing your message you save an attestation link and include it in the post/comment. This basic approach is deeply flawed, but hopefully better than nothing. I'm curious what current state of the art is for _guaranteeing_ that something is human typed. Perhaps some sort of hardware integration?

I'm working on a browser extension, and a quick way to integrate attestations with comment sections so users don't need to include the link copy/pasted. Would love any and all feedback.

p: https://www.ityped.it/p/RvRegYS453Sy

Comments URL: https://news.ycombinator.com/item?id=47172623

Points: 3

# Comments: 0

It's certainly not perfect, but similar to what you mention.

p: https://www.ityped.it/p/WIiTYfdxQ5ww

> can the agents check their email? other notification methods?

Yes to email (for paying customers agents spin up with unique addresses), no to other notifications, but as soon as a paying customer has a use case for SMS, etc. we'll build it.

I'd say this is one of our strong suits I think, specifically the UIs tend to be easy to navigate for browser agents, and the LLM as a judge offers pretty good feedback on chat quality and it can inform later actions. (I'd be remiss not to mention though that a good LLM eval framework like Braintrust is probably the best first line though)

> How do you handle testing onboarding flows?

We can step through most onboarding flows if you start from logged out state & give the context it'll need (i.e. a stripe test card, etc.) That said though, setting up integrations that require multi-page hops is still a pain point in our system and leaves a lot to be desired.

Would love to talk more about your specific case and see if we can help! founders@propolis.tech

To elaborate a little bit on the "canary" comment --

For a while at Airtable I was on the infra team that managed the deploy (basically click run and then sit and triage issues for a day), One of my first contributions on the team was adding a new canary analysis framework that made it easier to catch and rollback bugs automatically. Two things always bothered me about the standard canary release process:

1) It necessarily treats some users as lower value, and thus more acceptable to risk exposing bugs to (this makes sense for things like free-tier, etc. but the more you segment out, the less representative and thus less effective your canary is). When every customer interaction matters (as is the case for so many types of businesses) this approach is harder to justify

2) Low frequency / high impact bugs are really difficult to catch in canary analysis. While it’s easy to write metrics that catch glaring drops/spikes in metrics, more subtle high impact regressions are much harder and often require user reports (which we did not factor in as part of our canary). Example: how do you write a canary metric that auto rolls back when an enterprise account owner (small % of overall users) logs in and a broken modal prevents them from interacting with your website.

I view what we’re building at Propolis as an answer to both of these things. I envision a deploy process (very soon) that lets us roll out to simulated traffic and canary on THAT before you actually hit real users (and then do a traditional staged release, etc.)

Is any of your/their work published?

Right now it is available for free.

Would love feedback from Hacker News!

Comments URL: https://news.ycombinator.com/item?id=37893451

Points: 3

# Comments: 0

> This video is a feat of human intellect and ingenuity.

I couldn't agree more! Anyone reading this who can spare 20minutes - It's certainly worth it, and only escalates the longer you watch.

Comments URL: https://news.ycombinator.com/item?id=33726519

Points: 3

# Comments: 5

Formal language is certainly the most effective mode of communication for some things, but don’t discredit the value of other forms.

Also, this comment seems to discount the spirit of the post without offering any real reasons why.